Feature-Alignment-Based Cross-Platform Question Answering Expert Recommendation by Bin Tang, Qinqin Gao, Xin Cui, Qinglong Peng, Xu Yu

“…Extensive experiments are conducted on two real CQA datasets, Toutiao and Zhihu datasets, and the results show that compared to the other advanced expert recommendation algorithms, this paper’s method achieves better results in the evaluation metrics of MAE, RMSE, Accuracy, and Recall, which fully demonstrates the effectiveness of the method in this paper to solve the data sparsity problem in expert recommendation.…”
Get full text

Multi-View Clustering Based on Multiple Manifold Regularized Non-Negative Sparse Matrix Factorization by Mohammad Ahmar Khan, Ghufran Ahmad Khan, Jalaluddin Khan, Mohammad Rafeek Khan, Ibrahim Atoum, Naved Ahmad, Mohammad Shahid, Mohammad Ishrat, Abdulrahman Abdullah Alghamdi

“…The existing studies did not draw attention of over-fitting and sparsity among the diverse view, which is the considerable issue for getting the unique consensus knowledge from these complementary data. …”
Get full text

Block Sparse Bayesian Learning Based Joint User Activity Detection and Channel Estimation in Grant-Free MIMO-NOMA by Shuo Chen, Haojie Li, Lanjie Zhang, Mingyu Zhou, Xuehua Li

“…First, by fully mining the block sparsity of signals in the grant-free MIMO-NOMA system, we model the joint UAD and CE problem as a three-dimensional block sparse signal recovery problem. …”
Get full text

Energy-efficient video decoding using data statistics by Tikekar, Mehul (Mehul Deepak)

Get full text

Learning nonlocal sparse and low-rank models for image compressive sensing: nonlocal sparse and low-rank modeling by Zha, Zhiyuan, Wen, Bihan, Yuan, Xin, Ravishankar, Saiprasad, Zhou, Jiantao, Zhu, Ce

“…While classic image CS schemes employ sparsity using analytical transforms or bases, the learning-based approaches have become increasingly popular in recent years. …”
Get full text

Generic Hebbian ordering-based fuzzy rule base reduced neuro-fuzzy system with fuzzy rule interpolation (RS-Hebb+) by Yan, Hongxu

“…Neuro-fuzzy system, traditionally used in dynamic data sets modelling, is now evolving rapidly in both structure and style, including the trends from offline system changing to online system, and increasingly more concepts added to address issues like data sparsity, time-variants and non-linearity. As theoretical researches go on, the results have also been applied in a wild range of industries, including traffic control, rainfall prediction and financial markets. …”
Get full text

Bayesian nonparametric methods and applications in statistical network modelling by Miscouridou, X

“…The first random graph to allow sparsity as well as exchangeability was recently introduced by Caron and Fox [2017] whose framework we follow. …”

Quantum thermalization: anomalous slow relaxation due to percolation-like dynamics by Christine Khripkov, Amichay Vardi, Doron Cohen

“…This anomaly originates from an ℏ-dependent sparsity of the underlying quantum network of transitions. …”
Get full text

Reduced Order Modeling with Skew-Radial Basis Functions for Time Series Prediction by Manuchehr Aminian, Michael Kirby

“…We present a sparsity-promoting RBF algorithm for time-series prediction. …”
Get full text

A Simplified Convex Optimization Model for Image Restoration with Multiplicative Noise by Haoxiang Che, Yuchao Tang

“…Additionally, we impose an equality constraint on the data fidelity term, which simplifies the model selection process and promotes sparsity in the solution. We adopt the alternating direction method of multipliers (ADMM) method to solve the model efficiently. …”
Get full text

IP Core for Efficient Zero-Run Length Compression of CNN Feature Maps by A. Erdeljan, B. Vukobratović, R. Struharik

“…The OSM exploits the sparsity of data and implements two Zero-Run Length encoding algorithms and can be easily reconfigured to optimize usage for different CNN layers.…”
Get full text

Pseudo-Likelihood Estimation for Parameters of Stochastic Time-Fractional Diffusion Equations by Guofei Pang, Wanrong Cao

“…When only partial data is available, our approach can also attain acceptable results for intermediate sparsity of observation.…”
Get full text

Sparse Decomposition of Heart Rate Using a Bernoulli-Gaussian Model: Application to Sleep Apnoea Detection by Bruno H. Muller, Régis Lengellé

“…The problem of determining the BG series indicating the presence or absence of an event and estimating its amplitude is a deconvolution problem for which sparsity is imposed. This allows an almost syntactic representation of the heart rate on which simple detection algorithms are applied.…”
Get full text

Data Gathering Techniques for Wireless Sensor Networks: A Comparison by Giuseppe Campobello, Antonino Segreto, Salvatore Serrano

“…Moreover, we carry out simulations to validate our model and to compare the effectiveness of the above schemes by systematically sampling the parameter space (i.e., number of nodes, transmission range, and sparsity). Our simulation and analytical results show that there is no best data gathering technique for all possible applications and that the trade-off between energy consumptions and reliability could drive the choice of the data gathering technique to be used. …”
Get full text

An Improved Compression Sampling Matching Pursuit Algorithm by Fang LEI, Ze-sheng FANG, Yong-jun XU, Hong QIN, Jing-zhao Lü

“…In order to solve this issue, an improved Compressed Sampling Matching Pursuit (CoSaMP) algorithm is proposed by using the sparsity of the time-domain channel. Firstly, the initial channel estimation is performed by CoSaMP algorithm. …”
Get full text

Identification of railway subgrade defects based on ground penetrating radar by Zhezhe Hou, Weigang Zhao, Yong Yang

“…Abstract A recognition method is proposed to solve the problems in subgrade detection with ground penetrating radar, such as massive data, time–frequency and difference in experience. According to the sparsity of subgrade defects in radar images, the sparse representation of railway subgrade defects is studied from the aspects of the time domain, and time–frequency domain with compressive sensing theory. …”
Get full text

Quadratic hedging strategies for private equity fund payment streams by Christian Tausch

“…The application to US venture capital fund data further draws on a stability selection procedure to enhance model sparsity. Interestingly a natural connection to the famous Kaplan and Schoar (2005) public market equivalent approach can be established. …”
Get full text

Melissa: Bayesian clustering and imputation of single-cell methylomes by Chantriolnt-Andreas Kapourani, Guido Sanguinetti

“…Abstract Measurements of single-cell methylation are revolutionizing our understanding of epigenetic control of gene expression, yet the intrinsic data sparsity limits the scope for quantitative analysis of such data. …”
Get full text

Design of Protein Segments and Peptides for Binding to Protein Targets by Suchetana Gupta, Noora Azadvari, Parisa Hosseinzadeh

“…While the smaller size of these peptides allows for more exhaustive computational methods, flexibility in their structure and sparsity of data compared to proteins, as well as presence of noncanonical building blocks, add additional challenges to their design. …”
Get full text

Latent Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification by Kim, Been, Rudin, Cynthia, Shah, Julie

“…Simultaneously, LCM pursues sparsity by learning subspaces, the sets of few features that play important roles in characterizing the prototypes. …”
Get full text